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Tokenisation is the process of breaking up a given text into units called tokens.
What is tokenization in text processing. The tokens become the input for another process like parsing and text. It is one of the most foundational NLP task and a difficult one because every language has. Tokenization is one of the most common tasks in text processing.
It is one of the most foundational NLP task and a difficult one because every language has its own grammatical constructs which are often difficult to write down as rules. Building a thesaurus. What Does Tokenization Mean.
3 Removal of stop words. Tokenization is b reaking the raw text into small chunks. Tokenization is basically essential for breaking down text in natural language processing for enabling improved ease of learning.
A token may be a word part of a word or just characters like punctuation. Tokenization breaks the raw text into words sentences called tokens. There are many methods exist for tokenization.
So Its necessary to convert text to a number which machine can understand. One of the most important things to do before tackling any natural language processing task is text tokenization. As all of us know machine only understands numbers.
Tokens can be individual words phrases or even whole sentences. One can think of token as parts like a word is a token in a sentence and a sentence is a token in a paragraph. The various tokenization functions in-built into the nltk module itself and can be used in programs as shown below.
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